A typical computer network system includes a digital processor, main disk for storage and several work stations which are serviced by the digital processor and which share the information stored in the main disk. Each work station is coupled through a communication channel to the digital processor.
There are becoming more and more occasions for the transmission of digital analog signals such as image (video) data and sound (audio) data in such computer network systems. The speed at which image and sound data is transmitted is of paramount importance, particularly in situations where real time and playback is desired. There are generally two solutions that are typically used to decrease transmission time. One solution is to increase the bandwidth of the communication channel between the digital processor and work stations. A second solution is to compress the data prior to transmission. Datacompression in certain cases, however, is only effective if the decompression time is negligible in relation to the time saved in transmitting the data.
There are two main classes of image compression algorithms, known as lossy algorithms and exact algorithms. Lossy algorithms are those that produce a small difference between the original image or sound track and an image or sound track that has undergone a compression-decompression cycle. Exact algorithms are those that leave the image and sound completely unchanged in such a cycle.
Various types of compression encoding are also known in the state of the art. These include Huffman encoding, run length coding and Delta coding schemes. Huffman coding involves a multiplication operation and a variable code word size lookup to be performed for each decompressed sample. Other dictionary based encoding schemes also look at patterns of data and store the most frequently used patterns in a so-called "dictionary". A respective index is then used to look up each entry in the dictionary. To date, the application of these compression techniques to the problem of optimizing transmission of digitalized audio data is in need of improvement.